2015
DOI: 10.1002/jcp.24891
|View full text |Cite
|
Sign up to set email alerts
|

Anthropometric, Metabolic and Molecular Determinants of Human Epidermal Growth Factor Receptor 2 Expression in Luminal B Breast Cancer

Abstract: Genomic and trascriptomic profiling has recently contributed details to the characterization of luminal B breast cancer. We explored the contribution of anthropometric, metabolic, and molecular determinants to the multifaceted heterogeneity of this breast cancer subtype, with a specific focus on the association between body mass index (BMI), pre-treatment fasting glucose, hormone receptors, and expression of human epidermal growth factor receptor 2 (HER2). Extensively annotated specimens were obtained from 154… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1

Citation Types

0
4
0

Year Published

2015
2015
2018
2018

Publication Types

Select...
5

Relationship

5
0

Authors

Journals

citations
Cited by 5 publications
(4 citation statements)
references
References 44 publications
(50 reference statements)
0
4
0
Order By: Relevance
“…When addressing survival outcomes in the overall patient population, median PFS was 14 months (95% CI, [11][12][13][14][15][16][17], and median OS was 40 months (95% CI, 28-52). Survival outcomes were both affected by the molecular subtype ( Fig.…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…When addressing survival outcomes in the overall patient population, median PFS was 14 months (95% CI, [11][12][13][14][15][16][17], and median OS was 40 months (95% CI, 28-52). Survival outcomes were both affected by the molecular subtype ( Fig.…”
Section: Resultsmentioning
confidence: 99%
“…7 In light of the evidence emerged from recent literature and within our previously established research pipeline on the role of anthropometric and metabolic determinants of treatment efficacy in breast and ovarian cancer, we have now focused on a more restricted subgroup of patients from the original cohort with available data on body mass index (BMI) values at baseline assessment. [8][9][10][11][12][13][14][15] In this patient subgroup, data on several patient-and disease-related features were also analyzed and reinterpreted in light of the evidence emerging from the BMIrelated analysis. This study was designed and implemented within a real world setting.…”
Section: Introductionmentioning
confidence: 99%
“…On that occasion, beyond the limitations stemming from the retrospective study design, our findings fully replicated results from previous studies which were all verified at a real‐world population level (Cortes et al, ; Gamucci et al, ; Twelves et al, ; Kaufman et al, ). In addition, we have previously worked on the association of anthropometric and metabolic determinants with several disease‐ and patient‐related features with a renown prognostic and/or predictive value in breast cancer (Barba et al, ; Vici et al, , ). On this basis, the conduct of this study may be ideally placed at the exact confluence between these two research orientations.…”
Section: Discussionmentioning
confidence: 99%
“…In 2008, while the discussion on the concomitant administration of these two drugs was still extremely timely to a research agenda, we designed a phase II prospective trial of neoadjuvant chemotherapy with a sequential regimen of trastuzumab (T) and docetaxel (D) followed by trastuzumab and high‐dose epirubicin in combination with cyclophosphamide (EC), in patients with HER2‐positive operable or locally advanced breast cancer (DECT trial: Docetaxel, Epirubicin, Cyclophosphamide, Trastuzumab). In addition, given the growing interest of our research group towards the role played by anthropometric determinants in affecting treatment outcomes in breast cancer patients across different settings (Vici et al, ; D'Aiuto et al, ), we relied on data from the DECT trial to further test the association between baseline BMI and rate of pCR in HER2‐positive locally advanced or operable breast cancer and, more in general, to evaluate patient‐ and disease‐related features for their impact on treatment outcomes in the setting and population of interest.…”
mentioning
confidence: 99%